1. Field of the Invention
The present invention relates, in general, to laser radar, and, more particularly, to devices, systems and methods for measuring properties of multiple remote targets. Measured properties include one or more including position, range, velocity, reflectivity, polarization texture, or vibration.
2. Relevant Background
Most conventional lidar (light detection and ranging) and ladar (laser detection and ranging) sensor systems use a single laser beam to reflect off a remote target. Properties of the reflected light, detected at the sensor location, are used to extract information about the target. In the case of detecting range, time of flight ranging is commonly used, wherein the time taken for a short light pulse to travel to the target and back is measured. By detecting the state of polarization (SOP) of the reflected light compared to the transmitted light it is possible to extract information about man-made versus natural targets. Similar information may be obtained by measuring the reflectivity of the target compared with the surroundings. Velocity and vibration information can be obtained by detecting shifts in the radial (along the laser beam) position of the target with time, or through the use of Doppler frequency measurements. Such measurements are described, for example, in U.S. Pat. No. 5,237,331 to Henderson et al. and U.S. Pat. No. 5,815,250 to Thomson et al. which are incorporated herein by reference.
It is frequently desired to interrogate more than one point location in a field of view (FOV). This is useful in order to differentiate between desired target locations and the surrounding scene, as well as to conduct searches over a FOV for targets that have characteristics of interest for identification and/or classification purposes. It is therefore of interest to image a FOV or parts of a FOV by interrogating multiple points. Early generations of imaging systems utilized mechanical scanners to direct a single beam in such a manner that an image could be ‘painted’, for example by moving the beam in a raster pattern across a scene. Disadvantages of this approach include: rapid scanning is difficult to do quickly, especially if the transmitted beams are large, since the required mechanical hardware becomes heavy and large; mechanical scanners are subject to wear and reliability concerns; it is difficult to maneuver scans in arbitrary patterns rapidly; and it may be time consuming to scan a large FOV. The latter is a particular concern if the scene is changing rapidly or if the laser radar platform is moving rapidly, such as is often the case with laser radar systems mounted to aircraft that scan the ground. Moreover, collecting and analyzing the large amounts of data that can result from interrogating multiple points in a large scene is problematic.
To remedy this situation a great deal of effort has been directed to two areas. One is the development of non-mechanical scanning (NMS) techniques. These include micro-electro-mechanical (MEMS) devices, liquid crystals, and acousto-optic devices. It is noted that NMS techniques may solve some problems, for example less bulk and higher reliability, but they do not by themselves solve the problem of collecting data from a large scene rapidly and efficiently.
The second development area is directed at systems that collect data from numerous regularly spaced points in the FOV simultaneously. These are usually referred to as ‘flash’ imaging systems and operate similar to a conventional camera in that they collect a whole image at one time using detector arrays. Examples of such systems include publications by Marino et al. (pp.1 in Laser Radar Technology and Applications VIII, SPIE Proc. 5086, 2003) and Halmos (ibid. pp.70) which are incorporated herein by reference. Further examples are given by Landon in U.S. Pat. No. 5,353,109 where multiple beams are generated using a static diffractive device (Dammann gratings and holograms noted by the inventor) and also a system described in U.S. Pat. No. 5,610,705 to Brosnan and Komine which are incorporated herein by reference. By combining NMS techniques with flash imaging it is possible to relatively rapidly collect data from a large scene and to also point the ‘camera’ in the desired direction without the use of large and heavy mechanical means.
One problem with these prior approaches is that they do not provide sufficient flexibility to always be useful. In considering a general FOV it is often the case that most of the scene contains little or no information of interest. For example, a scene may contain several vehicles against a background filled with natural features. In this case one is typically interested in interrogating details of the vehicles, not the background. Illuminating the whole scene with light can then be extremely wasteful. For example, if the targets of interest only occupy 1% of the FOV then 99% of the illumination may be wasted. Not only is this wasting laser power in illumination, it also means that the electronics signal processor is spending much of its time performing calculations that are of no interest. Compounding the problem is that many lidar systems, especially those on board aircraft, have very limited electrical power and/or computational resources available. It is imperative that power usage be as efficient as possible in order to minimize the amount of illumination light that has to be provided. This in turn minimizes size, weight, cooling requirements, and system cost, as well as maximizing reliability by minimizing the number of system components.
A second problem with conventional approaches arises where the system uses coherent (e.g. heterodyne or homodyne) detection. In such cases a local oscillator (LO) laser beam is aligned carefully in position and angle with the return signal. Such alignment requirements normally account for a significant portion of the cost associated with designing coherent laser radar systems, even when only one LO beam has to be aligned properly. Scaling coherent imaging systems from a single pixel to, for example, imaging a FOV comprising 1,000×1,000=106 pixels requires providing LO beams for each pixel, which can become extremely complex. Furthermore, requiring that a local oscillator laser's power be divided to provide power to such large pixel counts can also put extraordinary demands on the LO laser, in order that sufficient power is provided on each pixel to achieve shot-noise limited detection sensitivity. The latter is highly desired to maximize detection of weak return signals from the target. In cases where the FOV contains mostly background information of relatively little interest, the system design would be considerably enhanced if only a selected subset of pixels were addressed.
A third problem may arise in the case of coherent lidar and is caused by the time delay between sending light to a target and receiving scattered light back. Since the speed of light in air is approximately 300,000 km/s, the round trip time is 67 μs for every 10 km distance to the target. Systems of this type are frequently operated in pulsed mode where short laser pulses are sent to the target. If the pulse spacing (inverse of the pulse repetition frequency or “PRF”) of the transmitter is shorter than the time taken for light from the previous pulse to return, for sufficiently distant targets a scanner may redirect the system to send a pulse in a different direction before the previous pulse is received back. Unless this is compensated for, the system will not be properly aligned and the detection efficiency will degrade considerably. A very similar problem arises from rapidly moving platforms, where the viewing angle may change rapidly, or for rapidly scanned systems, and is generally referred to as the ‘lag-angle’ problem. Even small angular misalignments between the transmitted and received beam paths, due to time lags between transmission and reception, cause degradation of the detection efficiency. If the scanning motion (or relative angular motion between the target and the system platform) is relatively constant, this can be compensated with through the use of fixed ‘lag-angle compensators’. An alternative method has been disclosed by Welch in U.S. Pat. No. 4,515,472 which are incorporated herein by reference. In the Welch method an array of local oscillator beams is generated to correspond to a variety of anticipated lag angles. In operation the intent is to ensure that even if the lag-angle is a priori unknown, the receive beam will match up with one of the generated LO beams and therefore detection can take place. A similar method has been disclosed by Meyzonnetie in U.S. Pat. No. 5,485,009 which are incorporated herein by reference. These approaches may have some use, but they do not solve the general problem of maximizing efficiency. If a large number of target points is illuminated and a large set of LO beams has to be generated for each pixel, the LO generation problem may become worse, rather than better.
A fourth problem that relates to the previously noted problems is that the volume of data may become difficult, impractical, or even impossible to process. For example, if a detector array has even 10,000 pixels (such as a 100×100 element array) and each pixel is sampled at, for example, 1 gigasamples per second (Gs/s), then the total data rate is 10 terasamples per second (Ts/s). This is not only difficult to process, it is also difficult to transfer from a detector chip to the processor and would likely lead to the construction of electronics that are far more complex, expensive, and bulky than desired. In cases where only a small fraction of the pixels carry information of interest, it becomes clear that this approach is inefficient. Much current effort is geared towards incorporation of pre-processing functionality into the detector/receiver arrays to reduce the computational loads on processors. In these implementations each detector pixel is coupled with a small electronics cell that performs desired pre-processing functions, such as amplification, filtering, thresholding, and the like.
One approach to the data reduction problem is to incorporate threshold detection into the electronics, such that only pixels that detect signals above some threshold would transfer the data out for further processing. In some circumstances this may work, but in other cases it does not. For example, coherent laser radar systems are typically purposely designed to operate in such a manner that only very weak signals are received, e.g. with receiver carrier-to-noise (CNR) levels near unity or even far less. The same situation is also true in many continuous-wave (CW) modulated cases. Signal recovery in these cases does not rely on a high instantaneous CNR but rather rely on the total signal collected over a predetermined measurement time. Since the CNR is so low, simple instantaneous intensity thresholding does not work and hence the approach of building thresholding circuitry into the receiver at the pixel level fails.
It should be noted that the detector arrays do not generally sample continuously at rates on the order of gigasamples/s so total data rates in the Tb/s range generally refers to input burst rates. The average rates may be significantly smaller yet the impact of receiving signals at very high rates nevertheless has a considerable impact on the design of the detector and receiver because the data is collected and stored at high speed even if it is transferred for post-processing at lower rates.